| Twenty-three unsolved problems in hydrology (UPH)–a community perspective G Blöschl, MFP Bierkens, A Chambel, C Cudennec, G Destouni, A Fiori, ... Hydrological Sciences Journal 64 (10), 1141-1158, 2019 | 269 | 2019 |
| Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores WJM Knoben, JE Freer, RA Woods Hydrology and Earth System Sciences 23 (10), 4323-4331, 2019 | 211 | 2019 |
| A Quantitative Hydrological Climate Classification Evaluated with Independent Streamflow Data WJM Knoben, RA Woods, JE Freer Water Resources Research 54 (7), 5088-5109, 2018 | 68 | 2018 |
| Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v1. 2: an open-source, extendable framework providing implementations of 46 conceptual hydrologic models as … WJM Knoben, JE Freer, KJA Fowler, MC Peel, RA Woods Geoscientific Model Development 12 (6), 2463-2480, 2019 | 45 | 2019 |
| DECIPHeR v1: dynamic fluxEs and connectivity for predictions of HydRology G Coxon, J Freer, R Lane, T Dunne, WJM Knoben, NJK Howden, N Quinn, ... Geoscientific Model Development 12 (6), 2285-2306, 2019 | 26 | 2019 |
| A brief analysis of conceptual model structure uncertainty using 36 models and 559 catchments WJM Knoben, JE Freer, MC Peel, KJA Fowler, RA Woods Water Resources Research 56, e2019WR025975, 2020 | 25 | 2020 |
| Global bimodal precipitation seasonality: A systematic overview WJM Knoben, RA Woods, JE Freer International Journal of Climatology 39 (1), 558-567, 2019 | 19 | 2019 |
| A global survey on the perceptions and impacts of gender inequality in the Earth and space sciences AL Popp, SR Lutz, S Khatami, THM Van Emmerik, WJM Knoben Earth and Space Science 6 (8), 1460-1468, 2019 | 17 | 2019 |
| Many commonly used rainfall‐runoff models lack long, slow dynamics: implications for runoff projections K Fowler, W Knoben, M Peel, T Peterson, D Ryu, M Saft, KW Seo, ... Water Resources Research 56 (5), e2019WR025286, 2020 | 15 | 2020 |
| Flexible vector-based spatial configurations in land models S Gharari, MP Clark, N Mizukami, WJM Knoben, JS Wong, A Pietroniro Hydrology and Earth System Sciences 24 (12), 5953-5971, 2020 | 11 | 2020 |
| Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models MI Brunner, LA Melsen, AW Wood, O Rakovec, N Mizukami, WJM Knoben, ... Hydrology and Earth System Sciences 25 (1), 105-119, 2021 | 6* | 2021 |
| DECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRology, Geosci. Model Dev., 12, 2285–2306 G Coxon, J Freer, R Lane, T Dunne, WJM Knoben, NJK Howden, N Quinn, ... | 6 | 2019 |
| DECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRology, Geosci. Model Dev., 12, 2285–2306, 10.5194 G Coxon, J Freer, R Lane, T Dunne, WJM Knoben, NJK Howden, N Quinn, ... gmd-12-2285-2019, 2019 | 6 | 2019 |
| Estimation of non-stationary hydrological model parameters for the Polish Welna catchment WJM Knoben University of Twente, 2013 | 6 | 2013 |
| Perceptions and impacts of gender inequality in the geosciences are strongly gendered A Popp, SR Lutz, S Khatami, T van Emmerik, WJM Knoben EarthArXiv, 2019 | 4 | 2019 |
| The abuse of popular performance metrics in hydrologic modeling MP Clark, RM Vogel, JR Lamontagne, N Mizukami, WJM Knoben, G Tang, ... Water Resources Research 57 (9), e2020WR029001, 2021 | 3 | 2021 |
| The numerical implementation of land models: Problem formulation and laugh tests MP Clark, R Zolfaghari, KR Green, S Trim, WJM Knoben, A Bennett, ... Journal of Hydrometeorology 22 (6), 1627-1648, 2021 | 2 | 2021 |
| Mimicry of a Conceptual Hydrological Model (HBV): What's in a Name? KF Jansen, AJ Teuling, JR Craig, M Dal Molin, WJM Knoben, J Parajka, ... Water Resources Research 57 (5), e2020WR029143, 2021 | 2 | 2021 |
| How do climate and catchment attributes influence flood generating processes? A large‐sample study for 671 catchments across the contiguous USA L Stein, MP Clark, WJM Knoben, F Pianosi, RA Woods Water Resources Research 57 (4), e2020WR028300, 2021 | 1 | 2021 |
| Process oriented insights from interpretable machine learning-what influences flood generating processes? L Stein, MP Clark, WJM Knoben, F Pianosi, R Woods Earth and Space Science Open Archive ESSOAr, 2020 | 1 | 2020 |
Ross WoodsUniversity of BristolVerified email at bristol.ac.uk
